The insurance industry is religiously governed by the law of averages. To be profitable, insurance companies must sell policies at premiums that will exceed the cost necessary to cover expected claims and operating expenses. Identifying the operating expenses for the insurance company is basic business management. However, identifying the expected claims that will arise from an insurance company's client base is a complex task. The typical insurance company has a team of actuarial scientist that pour through statistics, cost curves, trends, risk assessments, and a pocket protector full of other variables in an effort to accurately identify the risk of loss associated with particular client profiles or genres. Too many ill conceived projections can drag an insurance company into bankruptcy.
Thus, the insurance company is met with at least two competing interests or goals. On one hand, it needs to guaranty the reception of premiums adequate to keep the company profitable. On the other hand, the insurance company needs to offer price competitive programs that will attract a large number of clients. If the premiums for the insurance programs are set too low, the insurance company runs the risk of becoming cash poor. If the premiums for the insurance programs are set too high, the insurance company may not be able to attract enough clients to make the program worth while. The optimum scenario is to provide competitively priced programs to low risk clients. Therefore, there is a need in the art for a technique to help reduce the premiums of an insurance program while at the same time, reducing the risk attributed to insuring a particular entity.
The health care provider industry heavily relies on the insurance industry. Of particular interest is the long-term health care industry, such as nursing homes, elderly homes or the like. During the 1998 to 2000 time-frame, these long-term health care providers experienced insurance premium increases as high as 350% per year. One reason that these escalating premiums can be attributed to is the high-risk nature of the business. The number one claim levied against long-term health care providers are fall claims. In addition, wound care claims, such as bed sores, result in multimillion dollar judgments against the health care provider. These judgments are ultimately paid by the insurance companies.
The insurance risk of long-term health care providers dramatically increased with the implementation of the new Medicare system. When initially implemented, the rates offered by the Medicare system were drastically insufficient to meet the cost of the services provided. As a result, it was necessary for many long-term health care providers to reduce their nursing staff and to cut corners in obtaining proper medical equipment and supplies. Although corrective reimbursement changes have been made, this industry is still plagued with a high turnover rate of clinical and support personnel. The high turnover rate directly has an effect on the number of incidents that occur in such a long-term health care provider establishment.
High-risk entities, such as long-term health care providers are stuck in a “catch 22” situation. The providers cannot afford to provide the level of service necessary to reduce their insurability risks. Because of the high risk, the insurance premiums for such entities continue to escalate which results in increasing the insurability risk of the entity. Thus, there is a need in the art for a technique to help reduce the insurability risk of a long-term health care provider and to reduce the insurance premiums charged to the same.
Similar to the long-term health care industry, many other industries are also plagued by escalating insurance premiums do to their high-risk status. Thus there is a need in the art for a general technique that can help reduce the insurability risk of an entity and to provide affordable and profitable insurance programs to the entities.